To enable improved data interpretation, a series of finite element models have been prepared to simulate the effect of mentioned parameters on the results of various NDE tech- nologies using COMSOL Multiphysics software. The results of the finite element models were used to produce an algo- rithm that mitigates the effects of different parameters on the results of the HCP. The effect of two of the parameters—the moisture content and concrete cover thickness—is illustrated in Figure 10. The HCP results before and after applying the algorithm are shown in the same figure. The raw HCP data in Figure 10c shows that the middle area of the slab has high potential values (more negative values) indicating an antic- ipated high corrosion activity, while the edges tend to have fewer negative values. On the other hand, the HCP measure- ment is modified based on four different parameters: the degree of saturation, concrete cover, delamination depth, and electrical resistivity, which are shown in Figure 10d. It can be seen clearly that the algorithm has reduced the high potential voltages in the middle of the slab because this area has a thin concrete cover (25 to 38 mm, or 1 to 1.5 in.), as shown in Figure 9b, and also has a higher degree of saturation, as shown in Figure 9a. The reference model that was used to produce the algorithm is the model that has a 40% degree of saturation, a 50 mm concrete cover, and has no delamination as well as no corrosion in the reinforcement steel bar. In general, the algorithm has modified the HCP measurements by shifting the collected values to the right of the scale (fewer negative values), while the right and left edges had almost no changes in the potential values. The changes were primarily controlled by the effect of concrete cover thickness. Conclusion NDE will be essential for both the safety of bridges and their economic management. On the safety side, NDE technolo- gies enable the detection and characterization of defects and deterioration on fracture-critical bridge members. On the bridge management side, periodical NDE surveys enable the development of more reliable deterioration, predictive and life-cycle cost models and, thus, timely implementation of preventive maintenance, rehabilitation, and repair. To achieve wide acceptance of NDE in the condition assessment and monitoring of bridges, improvements are needed in the speed of data collection, the ability to deploy NDE technologies on hard-to-reach bridge components, and the NDE data inter- pretation. The first two will lead to a significant reduction in NDE survey costs, traffic interruptions, and risks for the bridge inspectors and drivers, while the third will lead to an accurate interpretation of the condition. The presented robotic systems are illustrations of the potential for improvements in the speed of data collection, simultaneous deployment of multiple NDE technologies, reduction in the number of bridge inspectors needed to ME | NDEOFBRIDGES Figure 10. Improved HCP results interpretation: (a) calibration curves for concrete cover and (b) degree of saturation and condition maps: (c) before and (d) after implementation of the algorithm. –500 –400 –300 –200 –100 0 mV Longitudinal distance (ft.) 21 17 13 9 5 1 1 5 9 13 17 21 25 29 33 37 41 45 49 –500 –400 –300 –200 –100 0 mV Longitudinal distance (ft.) 21 17 13 9 5 1 1 5 9 13 17 21 25 29 33 37 41 45 49 y = 1.576x2 – 2.3238x + 0.3857 0 0.1 0.3 0.5 0.7 0.9 0.05 0 –0.05 –0.10 –0.15 –0.20 –0.25 –0.30 –0.35 –0.40 –0.45 –0.50 Degree of Saturation % y = –0.0276x2 + 0.193x – 0.7765 –0.65 –0.60 –0.55 –0.50 –0.45 –0.40 0.5 1.5 2.5 3.5 Concrete Cover (in) 64 M AT E R I A L S E V A L U AT I O N • J A N U A R Y 2 0 2 3 2301 ME Jan New.indd 64 12/20/22 8:15 AM Transversedistance (ft. Transversedistance (ft. Voltage (V) Voltage(V)

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